基于小波去噪的微弱信号提取

小波分析理论是近几年来兴起的一种信号处理理论,已经成为信号去噪处理中的一种重要的工具.介绍了小波分析理论及其在信号去噪中的应用,并主要介绍了三种噪声处理方法:默认阈值法、强制阈值法和独立阈值法,运用小波分解与重构去噪方法,实现含噪信号的去噪处理.仿真结果证明:在信号分析中,利用小波变换来实现信噪分离提取弱信号是一种非常有效的方法.     

基于IIR小波滤波器的涡街流量计数字信号处理系统

涡街流量计被广泛应用于过程工业,但是,由于易受由管道振动和流场扰动等因素干扰,现场测量精度无法保证,测量小流量困难。本文将小波滤波器组应用于涡街流量计信号处理中,研究基于小波滤波的涡街信号处理方法,分析了小波滤波器的幅频特性对信号分析的影响,构造了幅频特性好的IIR型小波滤波器组。本文研制了基于ADSP2181的涡街流量计数字信号处理系统,并进行了气体流量和水流量标定实验,实验结果表明,基于小波滤波的涡街流量计数字信号处理系统有良好的适配性能,性能指标优于常规的涡街流量计处理系统。     

基于小波熵的微弱信号检测方法研究

在科学技术研究领域中,经常会遇到非平稳、低能量、瞬时变化的微弱信号检测问题,然而,微弱的有用信号往往被环境噪声所湮没,最大程度地提取有用信息一直是弱信号检测中的一个难题。尤其对短时低能量的瞬变信号,采用传统信号处理方法提取其位置信息难以奏效。小波分析的方法为弱信号检测技术开辟了一条新途径,但小波变换对弱信号进行特征提取的关键在于确定小波系数的阈值。为此,在软阈值基础上引入反映信号能量分布特性的小波熵概念,利用信号在不同分解尺度上具有不同的小波熵,能够自适应地确定高频系数分量的阈值。仿真分析表明,基于小波熵分析的方法能够在强噪声环境中对微弱信号准确定位,实现低能量的瞬变信号有效提取。     

基于小波除噪和经验模式分解的信号分析方法

经验模式分解是一种自适应分解算法。通过对常见信号的经验模式分解结果进行分析,发现信号中包含的噪声对分解结果影响较大。在此基础上,提出一种小波除噪与经验模式分解相结合的信号分析方法。该方法充分利用小波变换的降噪功能和经验模式分解的自适应分解能力,能真实地反映信号特征,为基于信号分析的故障诊断提供了一种可行的途径。     

Computationally lean algorithm of novel optimal FIR adaptive filter for vortex signal extraction

In a vortex flowmeter vortices are generated by a bluff body, inserted in the path of flow, which has a piezoelectric sensor embedded in it. This piezosensor develops a signal having a fundamental frequency that is proportional to flow. The flow measurement relies completely on extraction of true vortex signal and estimation of the correct frequency. A novel adaptive FIR filter has been designed and implemented using low power computational resource (8.25 mW), which gives better results than an existing contemporary system when tested on an industrial flow rig. Further more a comparative study of autocorrelation, EMD Scales filter and proposed algorithm is carried on the good and bad vortex signals. From this comparative study it is seen that proposed algorithm is effective for bad vortex signals and low flowrates where vortex signals are weak.     

基于区域化形态滤波的分合闸线圈电流信号特征值提取方法研究

针对断路器分合闸线圈电流信号特征值提取效率不能满足在线监测系统要求的问题,对断路器在线圈尺寸偏小、弹簧力矩偏小、线圈电阻偏大和控制电压偏低等4种故障下线圈电流信号的特点进行了归纳,说明了线圈电流信号区域化的可行性,对数学形态学的基本运算、结构元素及具备抗干扰能力的区间搜索求极值方法进行了研究,提出了一种数学形态滤波结合区间搜索求极值的特征值提取方法。利用ZF7A-12断路器实验平台分别进行了正常状态及4种故障状态实验以获取实验数据,并在Matlab中把该方法与传统小波结合求导方法进行了仿真对比。仿真结果表明:在5种状态下,该方法均能准确而高效地提取特征值,它与传统方法的特征值提取误差分别为4%和5%,同时其算法耗时仅为传统方法的25%。     

Extended stochastic resonance (SR) and its applications in weak mechanical signal processing

To catch symptoms of machine failure as early as possible, one of the most important strategies is to apply more progressive techniques during signal processing. This paper presents a method based on stochastic resonance (SR) to detect weak fault signal. First, a discrete model of a bistable system that can demonstrate SR is researched, and the stability condition for controlling the selection of model parameters of the discrete model and guarantee the solving convergence are established. Then, the frequency range of the weak signals that the SR model can detect is extended through a type of normalized scale transformation. Finally, the method is applied to extract the weak characteristic component from heavy noise to indicate the little crack fault in a bearing outer circle.     

Extended stochastic resonance (SR) and its applications in weak mechanical signal processing

To catch symptoms of machine failure as early as possible, one of the most important strategies is to apply more progressive techniques during signal processing. This paper presents a method based on stochastic resonance (SR) to detect weak fault signal. First, a discrete model of a bistable system that can demonstrate SR is researched, and the stability condition for controlling the selection of model parameters of the discrete model and guarantee the solving convergence are established. Then, the frequency range of the weak signals that the SR model can detect is extended through a type of normalized scale transformation. Finally, the method is applied to extract the weak characteristic component from heavy noise to indicate the little crack fault in a bearing outer circle.     

时变信号频率跟踪的一种新自适应陷波器方法

针对频率、幅值和相位均发生变化的时变信号,现有自适应陷波器(ANF)频率估计方法存在信号频率跟踪精确性和稳定性不足的问题,为此提出了一种基于新误差函数的ANF时变信号频率跟踪方法,通过新误差函数改善自适应算法收敛至最优频率解的精度与速度,以提高时变信号频率跟踪的精确性和稳定性。给出了新误差函数分析结果,新ANF方法实现步骤和该频率估计方法的Cramer-Rao下限。通过计算与现有ANF的时变信号频率跟踪方法性能进行了比较分析,并针对科里奥利质量流量计时变信号进行了现场实验验证。结果表明,该方法具有收敛速度快、跟踪精度高、更接近Cramer-Rao下限和抗噪性好的优点。     

基于小波包和HHT变换的声发射信号分析方法

针对声发射管道泄漏检测过程中的噪声干扰问题,对基于小波包和经验模态分解(EMD)的声发射信号处理方法进行了研究.采用小波包分解算法和经验模态分解都可以对管道泄漏声发射信号进行分解,但分解结果却存在一定区别.EMD是近年来非平稳信号分析领域的一个突破,对管道泄漏声发射信号进行EMD分解后,选择包含声发射特征的若干固有模式函数(IMF分量)进行重构,可以提取到管道泄漏声发射信号的本质特征,消除噪声信号的干扰.相对小波包分解方法而言,对根据IMF分量重构的声发射信号进行相关分析计算,得到的管道泄漏点的位置更为精确.     

Digital signal processing for a micromachined vibratory gyroscope based on a three dimensional adaptive filter demodulator

This paper reports a digital controller based on a three dimensional adaptive filter demodulator (AFD) for micromachined vibratory gyroscopes with the goal of eliminating common-mode noise and reducing hardware resources. The least mean square (LMS) adaptive filter, which has advantages of fast convergence speed, lower noise and fewer occupied hardware resources, is adopted to demodulate the vibration velocity of the gyroscope and detect its phase shift. A three dimensional AFD is proposed to eliminate the common-mode noise and quadrature coupling induced by the initial capacitance mismatch. Simulation and experimental results have verified the effectiveness of this method. The measurement results of the digital controlled gyroscope show a zero bias drift of 24.6 °/h and a nonlinearity of 0.1% with the measurement range of ±200°/s.     

A DSP-based signal processing method and system for CMF

A set of digital signal processing method is formed by combining a digital band-pass filter, an adaptive lattice notch filter and the DTFT algorithm considering negative frequency contribution for processing the signals of Coriolis mass flowmeter. A digital Coriolis mass flow transmitter is developed with a DSP chip to realize the signal processing approach. Some effective measures are proposed to ensure high accuracy and real time of this approach in the implementation. Simulations, electrical signal tests and water flowrate calibrations are conducted to validate the performances of the method and the system.     

A repeated single-channel mechanical signal blind separation method based on morphological filtering and singular value decomposition

This paper proposes a repeated blind source separation (BSS) method based on morphological filtering and singular value decomposition (SVD) to separate the mixed sources from a single-channel signal. Firstly the signal is de-noised by the morphological filter and, the noise which affects the accuracy of the separation is removed. Next, the purified signal is reconstructed in phase space, and the SVD is applied to this matrix. After choosing the effective singular values, the inverse transform is applied to the revised signal matrix. From this, the pseudo signal can be obtained. The pseudo signal and the purified original signal are used to achieve the mixed sources separation through the fast independent component analysis (FastICA) algorithm. Then, the methods above are repeated in order to separate the weaker signals. The analysis of simulation and practical application demonstrates that that proposed method shows a high level of separating performance of a single-channel signal.     

An adaptive Morlet wavelet filter for time-of-flight estimation in ultrasonic damage assessment

Ultrasonic non-destructive testing has been widely used in assessing the integrity of engineering materials such as high-temperature alloys and structures such as pipelines, bridges, and other load-bearing structures. The ultrasonic signals received from these structures are often noisy. Effective noise-reduction techniques are needed in order to accurately assess their condition. This paper presents a new digital signal processing method for estimating ultrasonic time-of-flight diffraction (TOFD). This method is based on wavelet analysis using the Morlet wavelet and the least mean squares (LMS) adaptive filter. The adaptive line enhancer (ALE) structure is used for the adaptive filter. The filter is designed to remove noise and identify the point at which the ultrasonic signal starts to reflect an echo from the tip of a crack. Both simulated and experimental data obtained from a steel plate with a crack produced by electrical-discharge-machining (EDM) are used to demonstrate the performance of the proposed method. This method is especially useful when the properties of the crack signal are unknown and the signal-to-noise ratio is low.     

自适应Morlet小波降噪方法及在轴承故障特征提取中的应用

分析了Morlet小波变换的滤波特性及其时频分辨率,利用Morlet小波良好的时域和频域特性及奇异值分解技术,提出了一种基于自适应Morlet小波和SVD的降噪方法。针对滚动轴承故障在振动信号中表现为冲击衰减波形的特点,采用修正的Shannon熵方法同时优化Morlet小波的中心频率与带宽参数,实现其与冲击特征成分的最优匹配;针对根据小波系数矩阵奇异值曲线的过渡阶段求取最佳变换尺度的方法存在着不够快捷方便的不足,将其与小波系数奇异值比方法相结合来快速方便地求得最佳变换尺度;最后对信号进行降噪处理提取故障特征。对仿真信号和实际轴承内外圈故障信号的应用分析表明,该方法具有良好的降噪性能,能有效地提取出滚动轴承的微弱故障特征。     

连通管式位移测量系统的小波信号处理研究

在连通管式位移测量系统中,液体振荡影响系统的位移测量精度。由于位移信号与液位振荡在时域和频域内均相互交叠,采用时域或频域分析方法都不能有效消除液位振荡的影响。为此,建立了连通管式位移测量系统输出信号的模型,结合液位振荡信号的特点,提出了针对确定性干扰信号去噪的小波阈值法。该方法的基本思想是：根据液位振荡的频率范围确定小波分解的尺度,在不同尺度上设定不同的阈值,以小波重构信号与原始信号的相关系数为目标来优化液位振荡频率所在尺度的阈值。通过对实际系统输出信号的小波分析表明,针对低频位移信号改进的小波阈值去噪方法非常适合于连通管式位移测量系统的信号分析,能够有效地消除液位振荡的干扰。     

基于弱控制信号分类强化的仿真机械手臂控制方法

针对当前的仿真机械臂控制系统中,存在的信号奇异性、强度退化等缺陷,提出一种基于弱控制信号强化的仿真机械臂控制方法,通过对多区域内,产生冲突的控制信号进行多重分形,对可能产生的冲突信号区域进行信号的强化处理,保证后期信号能够准确的到达识别区域,使得控制特征更加的明显。实验结果表明,该方法对复杂的控制信号种类实现了较为准确的划分强化,准确的控制仿真机械臂的后期动作,取得了理想的效果。     

基于小波变换及FFT算法的涡街信号处理

近年来涡街流量计的应用越来越广泛,但在实际使用时管道振动和流场扰动等引起的噪声易对涡街信号造成干扰,导致实际测量精度达不到要求。本文使用小波变换及FFT算法对涡街信号进行处理。该方法对涡街信号提取和去除噪声效果良好。有利于扩大涡街流量计的量程范围,提高测量精度。     

基于自适应卡尔曼滤波的光学监控信号处理

针对光学监控系统(OM S)实际工作环境的复杂性,导致监控信号中存在不稳定量测噪声,采用基于遗忘因子的自适应卡尔曼滤波(AKF)对光学膜厚监控信号进行去噪处理。建立了针对非线性OM S的AKF模型,仿真分析中针对存在突变信噪比(SNR)的输入信号设置相应AKF初始参数使滤波性能达到最优。结果表明自AKF输出监控信号精度明显优于常规卡尔曼滤波;同时利用AKF输出监控信号判读反射率极值点对应膜厚,最终理论膜厚监控误差<2nm。     

应用声光器件和光学滤波器实现电信号的实时子波变换

为实现输入电信号的实时传输,提出了应用声光器件和光学子波滤波器在光学范德拉格特(Vander Lugt)相关器中进行电信号实时子波变换的系统.选用的声光器件工作参数在正常布喇格区,可提高整个系统的信噪比,中心工作频率达100MHz.对变换系统中的主要参量进行了分析,认为系统需使用功率＞15 mW的激光器,且选用尺寸为1.8 mm的子波滤波器较为合适.给出了不同频率的电信号在含声光器件的二维Mexican-hat光学子波变换系统中的计算机模拟结果,表明所提出的系统能实现对输入电信号的实时子波变换.